Python for Data Science Training Course

The Intellipaat Python for Data Science training lets you master the concepts of the widely used and powerful programming language, Python. You will gain hands-on experience in working with various Python packages like SciPy, NumPy, Matplotlib, Lambda function and more. You will work on real-world projects in the domain of Python and apply it for various domains of Big Data, Data Science and Machine Learning.

Key Features

  • Instructor Led Training : 39 Hrs
  • Self-paced Videos : 24 Hrs
  • Exercises & Project Work : 50 Hrs
  • Get Certified & Job Assistance
  • Flexible Schedule
  • Lifetime free upgrade
  • 24 x 7 Lifetime Support & Access

About Python for Data Science Course

Intellipaat Python for Data Science training helps you learn the top programming language for the domain of Data Science. You will master the technique of how Python is deployed for Data Science, work with Pandas library for Data Science, do data munging and data cleaning, advanced numeric analysis and more through real-world hands-on projects and case studies.

What will you learn in this Python for Data Science training?

  1. Introduction to Python for Data Science
  2. OOP concepts, expressions and functions
  3. What is SQLite in Python, operations and classes
  4. Creating Pig and Hive UDF in Python
  5. Deploying Python for MapReduce programming
  6. Real-world Python for Data Science projects

Who should take up this Python for Data Science training?

  • BI Managers and Project Managers
  • Software Developers and ETL Professionals
  • Analytics Professionals
  • Big Data Professionals
  • Those who are wanting to have a career in Python

What are the prerequisites for learning Python for Data Science?

You don’t need any specific knowledge to learn Python. Though, a basic knowledge of programming can help.

Why you should take up this Python for Data Science training?

  • Python’s design and libraries provide 10 times productivity compared to C, C++ or Java
  • A Senior Python Developer in the United States can earn $102,000 – indeed.com

Python is one of the best programming languages that is used for the domain of Data Science. Intellipaat is offering the definitive Python for Data Science training course for learning Python coding, running it on various systems like Windows, Linux and Mac thus making it one of the highly versatile languages for the domain of Data Analytics. Upon the completion of the training, you will be able to get the best jobs in the Data Science domain for top salaries.

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Python for Data Science Course Content

Introduction to Data Science

What is Data Science, what does a data scientist do, various examples of Data Science in the industries and how Python is deployed for Data Science applications, various steps in Data Science process like data wrangling, data exploration and selecting the model.

Introduction to Python

Introduction to Python programming language, important Python features, how is Python different from other programming languages, Python installation, Anaconda Python distribution for Windows, Linux and Mac, how to run a sample Python script, Python IDE working mechanism, running some Python basic commands, Python variables, data types and keywords.

Hands-on Exercise – Installing Python Anaconda for the Windows, Linux and Mac

Python basic constructs

Introduction to a basic construct in Python, understanding indentation like tabs and spaces, code comments like Pound # character, names and variables, Python built-in data types like containers (list, set, tuple and dict), numeric (float, complex, int), text sequence (string), constants (true, false, ellipsis) and others (classes, instances, modules, exceptions and more), basic operators in Python like logical, bitwise, assignment, comparison and more, slicing and the slice operator, loop and control statements like break, if, for, continue, else, range() and more.

Hands-on Exercise – Write your first Python program, write a Python function (with and without parameters), use Lambda expression, write a class, create a member function and a variable, create an object and write a for loop to print all odd numbers

OOPs in Python

Understanding the OOP paradigm like encapsulation, inheritance, polymorphism and abstraction, what are access modifiers, instances, class members, classes and objects, function parameter and return type functions, Lambda expressions.

Hands-on Exercise – Writing a Python program and incorporating the OOP concepts

NumPy for mathematical computing

Introduction to mathematical computing in Python, what are arrays and matrices, array indexing, array math, Inspecting a numpy array, Numpy array manipulation,

Hands-on Exercise – How to import NumPy module, creating array using ND-array, calculating standard deviation on array of numbers and calculating correlation between two variables.

SciPy for scientific computing

Introduction to SciPy, building on top of NumPy, what are the characteristics of SciPy, various subpackages for SciPy like Signal, Integrate, Fftpack, Cluster, Optimize, Stats and more, Bayes Theorem with SciPy.

Hands-on Exercise: Importing of SciPy, applying the Bayes theorem on the given dataset.

Data manipulation

What is a data Manipulation. using Pandas library for data manipulation, NumPy dependency of Pandas library, Series object in pandas, Dataframe in Pandas, loading and handling data with Pandas, how to merge data objects, concatenation and various types of joins on data objects, exploring dataset, Cleaning dataset, Manipulating dataset, Visualizing dataset

Hands-on Exercise – Doing data manipulation with Pandas by handling tabular datasets that includes variable types like float, integer, double and others.

Data visualization with Matplotlib

Introduction to Visualization, Introduction to Matplotlib, Using Matplotlib for plotting graphs and charts like Scatter, Bar, Pie, Line, Histogram and more, Matplotlib API, Subplots and Pandas built-in data visualization.

Hands-on Exercise – Deploying Matplotlib for creating pie, scatter, line and histogram.

Machine Learning using Python

Revision of topics in Python (Pandas, Matplotlib, NumPy, scikit-Learn), Introduction to machine learning, need of Machine learning, types of machine learning, workflow of Machine Learning, Uses Cases in Machine Learning, its various arlogrithms, What is supervised learning, What is Unsupervised Learning,

Hands-on Exercise – Demo on ML algorithms

Supervised learning

What is supervised learning, What is linear regression, Step by step calculation of Linear Regression, Linear regression in Python, Logistic Regression, What is classification, Decision Tree, Confusion Matrix, Random Forest, Naïve Bayes classifier (Self paced), Support Vector Machine(self paced), xgboost(self paced)

Hands-on Exercise – Using Python library Scikit-Learn for coming up with Random Forest algorithm to implement supervised learning.

Unsupervised Learning

Introduction to unsupervised learning, use cases of unsupervised learning, What is clustering, Types of clustering(self-paced)-Exclusive clustering, Overlapping Clustering, Hierarchical Clustering(self-paced), What is K-means clustering, understanding the K-means clustering algorithm, Step by step calculation of k-means algorithm, Demo on k-means using Scikit , Association Rule Mining(self-paced), Market Basket Analysis(self-paced), Measures in association rule mining(self-paced)-support, confidence, lift, Apriori Algorithm, Demo on Apriori

Hands-on Exercise – Setting up the Jupyter notebook environment, loading of a dataset in Jupyter, algorithms in Scikit-Learn package for performing Machine Learning techniques and training a model to search a grid.

Python integration with Spark-(selfpaced)

Introduction to pyspark, who uses PySpark, need of spark with python, basics of pysark, Pyspark in industry, pySpark installation, pySpark fundamentals, advantage over mapreduce, pySpark Use-cases, and pySpark demo.

Hands-on Exercise: Demonstrating Loops and Conditional Statements, Tuple – related operations, properties, list, etc., list – operations, related properties, set – properties, associated operations, dictionary – operations, related properties.

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Python for Data Science Projects

What projects I will be working on this Python for Data Science training?

Project 1 : Analyzing the naming pattern using Python

Industry : General

Problem Statement : How to analyze the trends and most popular baby names

Topics : In this Python project you will work with the United States Social Security Administra4on (SSA) has made available data on the frequency of baby names from 1880 through 2016. The project requires analyzing the data considering different methods. You will visualize the most frequent names, determine the naming trends, and come up with the most popular names for a certain year.

Highlights :

  • Analyzing data using Pandas Library
  • Deploying Data Frame Manipulation
  • Bar & box plots with MatPlotLib.

Project 2 : – Python Web Scraping for Data Science

In this project you will be introduced to the process of web scraping using Python. It  involves installation of Beautiful Soup, web scraping libraries, working on common data and page format on the web, learning the important kinds of objects, Navigable String, deploying the searching tree, navigation options, parser, search tree, searching by CSS class, list, function and keyword argument.

Project 3 : Predicting customer churn in Telecom Company

Industry – Telecommunications

Problem Statement – How to increase the profitability of a telecom major by reducing the churn rate

Topics :In this project you will work with the telecom company’s customer dataset. This dataset includes subscribing telephone customer’s details. Each of the column has data on phone number, call minutes during various times of the day, the charges incurred, lifetime account duration, whether or not the customer has churned some services by unsubscribing it. The goal is to predict whether a customer will eventually churn or not.

Highlights :

  • Deploy Scikit-learn ML library
  • Develop code with Jupyter Notebook
  • Build a model using performance matrix.
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Sample Python for Data Science Video Tutorials

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Python For Data Science Certification

This course is designed for clearing the Intellipaat Python for Data Science Certification Exam. The complete course is created by industry experts for professionals to get the top jobs in the best organizations. The entire training includes real world projects and case studies that are highly valuable.

The Intellipaat Certification is awarded upon successfully completing the project work and after reviewing by experts. The Intellipaat certification is recognized in some of the biggest companies like Cisco, Cognizant, Mu Sigma, TCS, Genpact, Hexaware, Sony, Ericsson among others.

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Python for Data Science Training Reviews

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  1. Profile photo of payal.raheja Payal Raheja 

    The best Python for Data Science training

    I loved the way Intellipaat trainers taught the Python programming language as applicable to the Data Science domain. Great work!

  2. Profile photo of Alexane Hofer Alexane Hofer 

    Great support by Intellipaat

    I liked the dedication of the Intellipaat support team when it came to resolving my queries regardless of the time of the day. Hats off to team Intellipaat!

  3. Profile photo of PVKRAO Karunakara Rao P V 

    Best course ever

    This instructor-led training course is a beginner basic to advance in career. The trainer taught me all concepts from scratch. The study material really helped me to understand the subject properly. Hence, I believe this is the best course for beginners.

  4. Profile photo of Sahana CP Sahana CP 

    Awesome course.

    I am happy that Intellipaat provides flexible scheduling of classes. They gave immense support during my classes. I am happy with the course material and instructor’s way of teaching as well. I definitely recommend this course to everyone.

  5. Profile photo of imadhuri Madhuri Immaneni 

    Happy with project work.

    I got very good experience with the real-time projects provided by Intellipaat. The trainer was top class. The industry experience he carries is awesome. I am more than happy with the course. Looking forward to learn more Intellipaat online training courses.

Python for Data Science Course Advisor

Suresh Paritala

A Senior Software Architect at NextGen Healthcare who has previously worked with IBM Corporation, Suresh Paritala has worked on Big Data, Data Science, Advanced Analytics, Internet of Things and Azure, along with AI domains like Machine Learning and Deep Learning. He has successfully implemented high-impact projects in major corporations around the world.


David Callaghan

An experienced Blockchain Professional who has been bringing integrated Blockchain, particularly Hyperledger and Ethereum, and Big Data solutions to the cloud, David Callaghan has previously worked on Hadoop, AWS Cloud, Big Data and Pentaho projects that have had major impact on revenues of marquee brands around the world.


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Frequently Asked Questions about Python for Data Science

Why should I learn Python from Intellipaat?

This Intellipaat Python training will give you hands-on experience in mastering one of the best programming languages that is Python. In this online Python course, you will learn about the basic and advanced concepts of Python including MapReduce in Python, Machine Learning, Hadoop streaming and also Python packages like Scikit and Scipy. You will be awarded the Intellipaat Course Completion Certificate after successfully completing the training course.

As part of this online Python course, you will be working on real-time Python projects that have high relevance in the corporate world and step-by-step assignments, and the curriculum is designed by industry experts. Upon the completion of the Python online course, you can apply for some of the best jobs in top MNCs around the world at top salaries. Intellipaat offers lifetime access to videos, course materials, 24/7 support and course material upgrading to the latest version at no extra fees. Hence, it is clearly a one-time investment.

What are the different modes of training that Intellipaat provides?
At Intellipaat you can enroll either for the instructor-led online training or self-paced training. Apart from this Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience and they have been actively working as consultants in the same domain making them subject matter experts. Go through the sample videos to check the quality of the trainers.
Can I request for a support session if I need to better understand the topics?
Intellipaat is offering the 24/7 query resolution and you can raise a ticket with the dedicated support team anytime. You can avail the email support for all your queries. In the event of your query not getting resolved through email we can also arrange one-to-one sessions with the trainers. You would be glad to know that you can contact Intellipaat support even after completion of the training. We also do not put a limit on the number of tickets you can raise when it comes to query resolution and doubt clearance.
Can you explain the benefits of the Intellipaat self-paced training?
Intellipaat offers the self-paced training to those who want to learn at their own pace. This training also affords you the benefit of query resolution through email, one-on-one sessions with trainers, round the clock support and access to the learning modules or LMS for lifetime. Also you get the latest version of the course material at no added cost. The Intellipaat self-paced training is 75% lesser priced compared to the online instructor-led training. If you face any problems while learning we can always arrange a virtual live class with the trainers as well.
What kind of projects are included as part of the training?
Intellipaat is offering you the most updated, relevant and high value real-world projects as part of the training program. This way you can implement the learning that you have acquired in a real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning and practical knowledge thus making you completely industry-ready. You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. Upon successful completion of the projects your skills will be considered equal to six months of rigorous industry experience.
Does Intellipaat offer job assistance?
Intellipaat actively provides placement assistance to all learners who have successfully completed the training. For this we are exclusively tied-up with over 80 top MNCs from around the world. This way you can be placed in outstanding organizations like Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation part as well.
Is it possible to switch from self-paced training to instructor-led training?
You can definitely make the switch from self-paced to online instructor-led training by simply paying the extra amount and joining the next batch of the training which shall be notified to you specifically.
How are Intellipaat verified certificates awarded?
Once you complete the Intellipaat training program along with all the real-world projects, quizzes and assignments and upon scoring at least 60% marks in the qualifying exam; you will be awarded the Intellipaat verified certification. This certificate is very well recognized in Intellipaat affiliate organizations which include over 80 top MNCs from around the world which are also part of the Fortune 500 list of companies.
Will The Job Assistance Program Guarantee Me A Job?
In our Job Assistance program we will be helping you land in your dream job by sharing your resume to potential recruiters and assisting you with resume building, preparing you for interview questions. Intellipaat training should not be regarded either as a job placement service or as a guarantee for employment as the entire employment process will take part between the learner and the recruiter companies directly and the final selection is always dependent on the recruiter.
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